Abstract 5374
Background
We aimed to validate the prognostic effects of the metastatic lymph nodes ratio (LNR) in patients with gastric neuroendocrine tumour (G-NET), and establish a nomogram to predict the survival of patients.
Methods
A total of 315 patients with G-NET in the Surveillance, Epidemiology, and End Results (SEER) database from 2004 to 2015 were included. Pearson correlation and Cox regression were performed to identify the association between LNR and survival. Nomograms were adopted to predict overall survival (OS) and cancer-specific survival (CSS).
Results
LNR has a negative correlation with OS and CSS (Pearson correlation coefficients: 0.343, P < 0.001; 0.389, P < 0.001, respectively). The multivariate analyses indicated age, tumour site, differentiation, T staging, M staging, chemotherapy and LNR were independent prognostic factors for both OS and CSS. The concordance index (C-index) of the nomograms for OS and CSS were superior to those of the TNM classification (0.773 vs. 0.731; 0.807 vs. 0.769, respectively). According to the area under the ROC curve (AUC), the predictive ability of the new nomogram for 3- and 5-year OS was better than TNM classification (0.908 vs. 0.846, P = 0.004; 0.899 vs. 0.827, P < 0.001, respectively). And the predictive ability of the new nomogram for 1-, 3- and 5-year CSS was better than TNM classification (0.936 vs. 0.848, P = 0.007; 0.910 vs. 0.855, P = 0.003; 0.894 vs. 0.836, P = 0.001, respectively).
Conclusions
LNR was an independent predictor of OS and CSS in G-NET. The nomograms based on the LNR were superior to the TNM classification in predicting the clinical outcomes for G-NET patients.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
Yaobin Lin.
Funding
The Fujian Province Natural Science Foundation (2017J01260), Joint Funds for the Innovation of Science and Technology, Fujian province (2017Y9074), and the Peking University Cancer Hospital & Institute, Key Laboratory of Carcinogenesis and Translational Research, Ministry of Education/Beijing (2017 Open Project-9).
Disclosure
All authors have declared no conflicts of interest.
Resources from the same session
4732 - Progesterone Receptor Isoform Ratio Dictates Antiprogestins/Progestins Effects on Metastatic Breast Cancer Models
Presenter: Maria Abascal
Session: Poster Display session 2
Resources:
Abstract
5737 - PAM50 and CGH-array genomic characterization of HER2-Equivocal Breast Cancers defined by the 2018 ASCO/CAP recommendations.
Presenter: Carine Ngo
Session: Poster Display session 2
Resources:
Abstract
1096 - OncotypeDX® predictive nomogram for recurrence score output: a machine learning system based on quantitative immunochemistry analysis - ADAPTED01
Presenter: Fabio Marazzi
Session: Poster Display session 2
Resources:
Abstract
5426 - Geriatric parameters predict both disease-related and patient-reported outcomes in older patients with breast cancer
Presenter: Willeke van der Plas-Krijgsman
Session: Poster Display session 2
Resources:
Abstract
5865 - Patients with a 21-gene assay in South East London differ from the TAILORx trial population
Presenter: Charalampos Gousis
Session: Poster Display session 2
Resources:
Abstract
1312 - Predictive tools in adjuvant breast cancer – what is the standard of evidence supporting their utility? A literature review examining validation of Adjuvant!, Cancermath and NHS Predict
Presenter: Alice Loft
Session: Poster Display session 2
Resources:
Abstract
2445 - Oncologic outcome of invasive lobular carcinoma: Is it different from that of invasive ductal carcinoma?
Presenter: Hee Jun Choi
Session: Poster Display session 2
Resources:
Abstract
2476 - Pathologic response and survival efficacy in patients with initial nodal involvement after neoadjuvant chemotherapy in early breast cancer
Presenter: SERAFIN MORALES Murillo
Session: Poster Display session 2
Resources:
Abstract
3761 - Chemotherapy-induced amenorrhea: prognostic impact on premenopausal Egyptian patients with breast cancer
Presenter: Khaled Abdel Karim
Session: Poster Display session 2
Resources:
Abstract
4687 - Predicting the presence of breast cancer using circulating small RNA in the serum
Presenter: Yumiko Koi
Session: Poster Display session 2
Resources:
Abstract